Borrowing it
Nothing to install: this file belongs to loerei/chronicle-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/loerei/chronicle-mcp/main/.agents/skills/taste-skill/SKILL.mdgit clone --depth 1 https://github.com/loerei/chronicle-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/loerei/chronicle-mcp/taste-skill)<a href="https://agentmods.dev/skills/loerei/chronicle-mcp/taste-skill"><img src="https://agentmods.dev/badge/skills/loerei/chronicle-mcp/taste-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/loerei/chronicle-mcp/taste-skill"><img src="https://agentmods.dev/badge/skills/loerei/chronicle-mcp/taste-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.08730 |
| Opus 5 | $0.00000 | $0.04365 |
| Sonnet 5 | $0.00000 | $0.01746 |
| Haiku 4.5 | $0.00000 | $0.00873 |
Grade A, and why
taste-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to enhance-web-landing — 275 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: design-taste-frontend description: Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
tasteskill: Anti-Slop Frontend Skill
Landing pages, portfolios, and redesigns. Not dashboards, not data tables, not multi-step product UI. Every rule below is contextual. None of it fires automatically. First read the brief, then pull only what fits.
0. BRIEF INFERENCE (Read the Room Before Anything Else)
Before touching code or tweaking dials, infer what the user actually wants. Most LLM design output is bad because the model jumps to a default aesthetic instead of reading the room.
0.A Read these signals first
- Page kind - landing (SaaS / consumer / agency / event), portfolio (dev / designer / creative studio), redesign (preserve vs overhaul), editorial / blog.
- Vibe words the user used - "minimalist", "calm", "Linear-style", "Awwwards", "brutalist", "premium consumer", "Apple-y", "playful", "serious B2B", "editorial", "agency-y", "glassy", "dark tech".
- Reference signals - URLs they linked, screenshots they pasted, products they named, brands they're competing with.
- Audience - B2B procurement panel vs. design-conscious consumer vs. recruiter scanning a portfolio. The audience picks the aesthetic, not your taste.
- Brand assets that already exist - logo, color, type, photography. For redesigns, these are starting material, not optional input (see Section 11).
- Quiet constraints - accessibility-first audiences, public-sector, regulated industries, trust-first commerce, kids' products. These constraints OVERRIDE aesthetic preference.
0.B Output a one-line "Design Read" before generating
Before any code, state in one line: "Reading this as: <page kind> for <audience>, with a <vibe> language, leaning toward <design system or aesthetic family>."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 339 lines · 0 tokens per session scan A 3768353b7717
taste-skill is a skill published in the GitHub repository loerei/chronicle-mcp (0 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 8,730 tokens. A static security scan graded it A with 0 findings. It is 88% identical to enhance-web-landing, differing in 275 lines, and is treated as a copy.
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